The Impact of Experiences and Perceptions of Highly Pathogenic Avian Influenza (HPAI) on Water‐Related Biosecurity Behaviour in Rural Vietnam
Bibliographic record
Abstract
BACKGROUND: In Southeast Asia from 2004 to 2006, highly pathogenic avian influenza (HPAI) resulted in culling 45 million birds and jeopardizing sustainable agricultural production. HPAI is highly virulent; small-scale farms present a high-risk environment for disease transmission between animals and humans. We investigated how attitudes toward HPAI influence water-related biosecurity mitigation behaviors on small-scale farms in Vietnam using the conceptual framework Social Cognitive Theory. METHOD: We analyzed a secondary cross-sectional data set from northern (Thai Binh) and southern (An Giang) provinces in Vietnam, describing a stratified randomized selection of 600 small-scale farmers who were interviewed using questionnaires and in-person interviews. Logistic regression analysis and odds ratios were used to examine relationships between factors influencing HPAI attitudes, social norms, perceived importance, and behaviors (α = 0.10) RESULTS: Concern about the severity of HPAI was significantly associated with increased perceived importance for all water management biosecurity methods (p < 0.01). Media and/or peer influence had negative effects on perceived importance to practice water-related biosecurity (p < 0.10). High importance of practice water-related biosecurity resulted in high uptake (p < 0.05). Past experiences with HPAI were significant in predicting perceived importance; none were significant in describing behavior uptake. DISCUSSION: Biosecurity guidelines may not be consistent with management styles of Vietnamese small-scale farms; perceived importance of a behavior may be an important mediating variable. Gaps exist in uptake of water management practices as biosecurity for HPAI, potentially negatively affected by peer and media influence. Our results should be of interest to public health and policy authorities addressing HPAI mitigation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".